Operational Predictive Maintenance Market Chief Industry Participants Include General Electric Company, IBM Corporation, eMaint Enterprises LLC, Software AG, Schneider Electric SE, SAS Institute Inc., Rockwell Automation Inc., PTC, Inc., and Robert Bosch

Market Overview
Operational predictive maintenance refers to a practice of determining the risk of failures in an operational process. In this, predicative analytics software and services access multiple data sources in real-time, in order to identify asset failure and quality issues in product development process. Moreover, predicative analytics software evaluates failure patterns and minor variances, in order to determine the risk of failures in operational process in order to reduce or avoid future losses.
The global operational predictive maintenance market was estimated to account for US$ 1,138.4 Mn in terms of value by the end of 2019

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Market Dynamics- Drivers

Growing awareness regarding maintenance operation and reducing asset downtime is expected to drive growth of the global operational predictive maintenance market during the forecast period
In industrial facilities, managers are constantly focused on enhancing maintenance process at manufacturing plants and other operating ecosystems. Facility manager can prevent virtual downtime with predictive maintenance, especially when the equipment is not operating to its maximum potential Moreover, predictive maintenance system can control various types of data including temperature, energy use, output, run time, etc. to enhance decision making and operations at manufacturing plants or manufacturing units.

Growing implementation of new technologies is expected to propel the global operational predicative maintenance market over the forecast period

Technology-based ERP software solutions are developed for enterprises for predictive maintenance and to enhance their efficiency.
Numerous energy-based manufacturing plants have implemented operational predictive maintenance solution. Moreover, many public sector and manufacturing companies are rapidly implementing new technologies, in order to predict failures and reduce losses related to it. These factors are expected to boost the market growth in the near future.

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Market Opportunity

Advancement in cloud-based solution targeting new industries is expected to pose lucrative business opportunity for market players in the near future
Growing adoption of operational predictive maintenance solutions by small and mid-sized enterprises (SMEs)

Market Trends

1. Partnerships and mergers and acquisitions among key market players

Key companies in the market are focused on partnerships and mergers and acquisitions, in order to enhance their market presence. For instance, in September 2016, Fluke Corporation, an electronic test tools and software providing company, acquired eMaint Enterprises LLC. In September 2016, Robert Bosch GmbH partnered with SAP SE, in order to expand their product portfolio based on IoT and Industry 4.0, and cloud technologies and software solutions.

2. New product launches by key market players
Key players in the market are involved in product development and launches, in order to expand their product portfolio and gain competitive advantage in the market. For instance, in April 2016, SAS Institute, Inc. introduced Viya, an analytics and visualization architecture platform for businesses, for government agencies and other organizations for a single, open, and cloud-ready architecture.

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Competitive Section

Key companies in the global operational predictive maintenance market are General Electric Company, IBM Corporation, eMaint Enterprises LLC, Software AG, Schneider Electric SE, SAS Institute Inc., Rockwell Automation Inc., PTC, Inc., and Robert Bosch GmbH.

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